If you are using LLMs to interact with sites like GitLab and GitHub, and you have the option to use a GraphQL API, you should jump on it immediately.
GraphQL is absolutely terrible for human developers to interact with, but it's like Facebook could see into the future back in 2012. I cannot imagine a more perfect API surface for agents. With the REST API on GitHub, you can consume maybe 10 issue JSON blobs before your context window is blown out. With GraphQL constraining the results you can easily read hundreds in the same token budget.
Additionally, the # of requests your agents need to make can be reduced in many cases since GraphQL can join across types whereas REST APIs cannot. You essentially get savings in two dimensions here. Quota and raw token volume per logical response.
It depends. There are hidden limits in GitHub’s gql. Some will time out above certain quantities and it’s not documented, which probably means it’s a significant server strain to serve the successful responses. I find I have to maintain a test suite to probe those limits. All this makes REST continue to be appealing if testing the gql load for a service hints at any uncertain limits/instability.
bob1029 · · focus · HN ↗
GraphQL is absolutely terrible for human developers to interact with, but it's like Facebook could see into the future back in 2012. I cannot imagine a more perfect API surface for agents. With the REST API on GitHub, you can consume maybe 10 issue JSON blobs before your context window is blown out. With GraphQL constraining the results you can easily read hundreds in the same token budget.
Additionally, the # of requests your agents need to make can be reduced in many cases since GraphQL can join across types whereas REST APIs cannot. You essentially get savings in two dimensions here. Quota and raw token volume per logical response.
1123581321 · · focus · HN ↗